 | M. de Almeida, C. Samarawickrama, N. de Silva, G. Ratnayaka, and A. Perera
2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), IEEE, 2020, pp. 143--148, [pdf] [bib]
In the field of natural language processing, domain specific information retrieval using given documents has been a prominent and ongoing research area. The automatic extraction of the legal parties involved in a legal case has a significant impact on the proceedings of legal cases. This is a study proposing a novel way to extract the legal parties involved in a given legal document. The motivation behind this study is that there is the absence of a proper automated system to accurately identify the legal parties in a legal document. We combined several existing natural language processing annotators together with a sequence to sequence learning model to achieve the goal of extracting legal parties in a given court case document. Then, our methodology was evaluated with manually labeled court case sentences. The outcomes of the evaluation demonstrate that our system is successful in identifying legal parties. |
